About Facebook Places and why Foursquare, Gowalla, Qype and Yelp will continue to strive

Most likely, you've read about Facebook Places one way or another in the last couple days, even if you aren't a techgeek. After all the service is ultimately going to become available to about 8% of the world's population. So quite hard to avoid. But if you missed it, GigaOm did a good debrief here.

For now it's only available in the US, so I've only managed to get second hand experiences so far, but that didn't stop me from pondering whether and how I will use this new service, the impact it may have on other swimmingly similar services such as Yelp, Qype, Foursquare, Gowalla and the others and most importantly, what it means for businesses.

How will I use it?
I've been an early adopter of check-in based services, from always-on Google Latitude to action based Foursquare and Qype. I discovered that the service I used and the reasons for using it was heavily dependant on two things: the graph model and the graph members. Let me explain what I mean here.

• The relevance of the model: Facebook is by default mostly closed to the world. So things I post on my stream, I expect only my Facebook friends to see. On the other side of the spectrum is Twitter. Things I post on Twitter, I expect the entire webuniverse to see. In the middle, you have Latitude, Foursquare, Gowalla, Qype, Yelp and the others. There are some check-ins I will share only with my family or friends, some other that I will share with business contacts and some I don't mind sharing with the world at large. Different use cases, different models required.
  
• The graph members: I am also quite conscious that I don't want to pollute people screen estate with information that isn't relevant to them. As an example, when I was earlier this year at SXSW Interactive talking about how LikeCube powered recommendations for locations, Foursquare and Gowalla made a lot of sense to use, because 1-I needed an open model where I could find people easily and they could find me, 2-I needed a graph that was mostly business oriented and relevant with my time in Austin, TX (my business contacts from my days in IT services couldn't care less that I attended a panel on the future of geolocation). Foursquare and Gowalla adressed these needs well because most of the people there used one or the other service and these graph members were most not present in my Facebook or twitter graphs... or Linkedin graph for the matter.
  

Are the other services affected?
Well is it quite early to say, but in my personal case, because of the way I use my Facebook graph, I will continue to use Qype (for getting personalized recommendations to discover new places), Foursquare and Gowalla (for staying in touch with my SXSW extended crowd) and hopefully one day Linkedin. But maybe overtime, someone will solve the issue of how to manage all those graphs with respect to the business cases we use them for and I might revert to a single service.

So what does it mean for businesses?
The big opportunity is of course related to cracking to local advertising space. With the dismiss of the print Yellow Pages, a void was left. Google, Yelp and Qype have built their business on this. Now Foursquare and Gowalla are getting there through game mechanics and the check-in revolution. Now Facebook is clearly set on taking it to another level. With an unrivalled reach of 500m users, it will be interesting to see how things will evolve. You can find some advices on what to do with Facebook Places here.

Personally, I think that until such time one of these players manages to get the graphs playing nice with the business cases so that everyone adopt only one, you'll still have to consider what each player can do for you individually. Each is specific and can help you reach a different audience. So know your targets!

Hotel industry in need of data or innovation?

In a recent interview from Sandeep Govil and Natasa Christodoulidou, the author was talking about the need to better understand your customer interaction with the hotel booking sites. Essentially, "hotels have a long way to go in talking to guests about the product, its attributes, locale, etc. in a way that each individual guest wishes to receive that information"

According to Natasa, "the key to working on CRM data gathering approaches in a manner that engages the customer as little as possible while obtaining the information that makes the biggest impact on the goals as a service provider is simply personalisation".

It is clear that there is a lot of value from capturing more data, as long as data is available. However, there is a significant challenge in the hotel industry. One that I usually describe with the number 4.

If users have used a site less than 4 times, then they are unlikely to use it by default for their next booking. They simply don't have much loyalty to the site yet.

Above 4, the users become more loyal to the site and use it as a natural starting point to their hotel research.

Now this is clearly over-simplifying a complex problem for marketers and CRM experts. But I think it's worth the analysis.

So in terms of numbers what does it means. Well the below 4 represent 95% of the bookings. 95%. To give you another representation of the challenge, the average number of bookings per user is below 2... Building user statistical patterns with such a low amount of data is unreliable. Hence the challenge of marketers and CRM specialists.

Now there is an interesting parallel that can be done here. 4 is also the number at which personalization solutions based on collaborative filtering (people who like the same hotels I liked also liked...) start showing interesting levels of accuracy and related impact on conversion rates. Before 4, consider yourself in a cold start situation.

We've addressed both sides of the challenge at LikeCube.

Leveraging our expertise in semantics, ontology and search, we provide very innovative solutions to address the cold start issue. Rather than asking data and trying to profile users as suggested by Natasha, our SaaS solution enables hotel sites to offer a powerful way for users to express their preferences and filter their results accordingly. Conversion rate improvements are expected to be of the order of 10% to 20%.

And for users that have crossed the '4' gap, our state of the art collaborative filtering solution could up conversion rate significantly more. The other key benefit here is that users get the noise filtered out automatically, including reviews and other form of user generated content. This of course results in drastically improved user experience. They will see first the content from their taste neighbors, the people most like them in terms of preferences, as opposed to hundred of reviews, most of which are non relevant to them.

So how are you going to differentiate from your competition to secure the 95% of users that are in cold start? And what are you doing to leverage your investment in UGC? Is data or innovation the answer?

Feel free to contact us at info@likecube.com for your free Site-Matcher evaluation.